sample_embeddings_azure_openai.py

# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------
"""
DESCRIPTION:
 This sample demonstrates how to get text embeddings for a list of sentences
 using a synchronous client, with an Azure OpenAI (AOAI) endpoint.
 Two types of authentications are shown: key authentication and Entra ID
 authentication.

USAGE:
 1. Update `key_auth` below to `True` for key authentication, or `False` for
 Entra ID authentication.
 2. Update `api_version` (the AOAI REST API version) as needed.
 See the "Data plane - inference" row in the table here for latest AOAI api-version:
 https://aka.ms/azsdk/azure-ai-inference/azure-openai-api-versions
 3. Set one or two environment variables, depending on your authentication method:
 * AZURE_OPENAI_EMBEDDINGS_ENDPOINT - Your AOAI endpoint URL, with partial path, in the form 
 https://<your-unique-resouce-name>.openai.azure.com/openai/deployments/<your-deployment-name>
 where `your-unique-resource-name` is your globally unique AOAI resource name,
 and `your-deployment-name` is your AI Model deployment name.
 For example: https://your-unique-host.openai.azure.com/openai/deployments/gpt-4o
 * AZURE_OPENAI_EMBEDDINGS_KEY - Your model key. Keep it secret. This
 is only required for key authentication.
 4. Run the sample:
 python sample_embeddings_azure_openai.py
"""


defsample_embeddings_azure_openai():
importos
fromazure.ai.inferenceimportEmbeddingsClient

try:
endpoint=os.environ["AZURE_OPENAI_EMBEDDINGS_ENDPOINT"]
exceptKeyError:
print("Missing environment variable 'AZURE_OPENAI_EMBEDDINGS_ENDPOINT'")
print("Set it before running this sample.")
exit()

key_auth=True# Set to True for key authentication, or False for Entra ID authentication.

ifkey_auth:
fromazure.core.credentialsimportAzureKeyCredential

try:
key=os.environ["AZURE_OPENAI_EMBEDDINGS_KEY"]
exceptKeyError:
print("Missing environment variable 'AZURE_OPENAI_EMBEDDINGS_KEY'")
print("Set it before running this sample.")
exit()

client=EmbeddingsClient(
endpoint=endpoint,
credential=AzureKeyCredential(key),
api_version="2024-06-01", # Azure OpenAI api-version. See https://aka.ms/azsdk/azure-ai-inference/azure-openai-api-versions
 )

else: # Entra ID authentication
fromazure.identityimportDefaultAzureCredential

client=EmbeddingsClient(
endpoint=endpoint,
credential=DefaultAzureCredential(exclude_interactive_browser_credential=False),
credential_scopes=["https://cognitiveservices.azure.com/.default"],
api_version="2024-06-01", # Azure OpenAI api-version. See https://aka.ms/azsdk/azure-ai-inference/azure-openai-api-versions
 )

response=client.embed(input=["first phrase", "second phrase", "third phrase"])

foriteminresponse.data:
length=len(item.embedding)
print(
f"data[{item.index}]: length={length}, [{item.embedding[0]}, {item.embedding[1]}, "
f"..., {item.embedding[length-2]}, {item.embedding[length-1]}]"
 )


if__name__=="__main__":
sample_embeddings_azure_openai()